一、个人简介：

陈雪蓉，西南财经大学“光华杰出学者计划”青年杰出教授、博士生导师，国家级青年人才计划入选者，省级高层次人才入选者。中科院数学与系统科学研究院博士（联合培养），美国密苏里大学统计系、乔治城大学生物统计博士后，美国密歇根大学、香港城市大学、香港大学访问学者。论文发表于JASA, Biometrics, Journal of Business & Economic Statistic等统计学、生物统计学、计量经济学权威期刊。主持国家自然科学基金面上项目2项、青年项目、国家自然科学基金重点项目子课题、国家重点研发计划课题子课题各1项。曾荣获教育部“第八届高等学校科学研究优秀成果奖青年成果奖”。

二、研究方向：

统计机器学习，大数据分析、隐私保护、生物统计、半参数非参数建模、复杂数据分析

三、教授课程：

本科生：多元统计分析、分类数据分析、非参数统计

硕士生：广义线性模型、非参数统计、隐私保护、生存分析

博士生：大样本理论、数据科学基础、缺失数据

四、招生信息：

热忱欢迎有志从事统计学、数据科学行业、数学基础扎实、编程能力强（熟练掌握R、Python、Matlab或C之一）、具有团队合作精神及吃苦耐劳精神的本科生、硕士生及博士生加入我的团队。我将资助博士生（每个博士生不少于两次）及优秀的硕士生参加学术会议、专业培训及暑期学校。

五、学术成果：

[27]Chen, X., Ping, Y. and Sun, J.(2023) .Efficient estimation of Cox model with random change point.Statistics in Medicine. To appear

[26]Lan,W.,Chen, X., Zou, T. and Tsai, C-L.(2022) . Imputations for High Missing Rate Data in Covariatesvia Semi-supervised Learning Approach.Journal of Business and Economic Statistics, 40, 1282-1290.

[25]Chen, X., Leung, H. and Qin, J.(2022). Nonignorable missing data, single index propensity score anda profile synthetic distribution function method.Journal of Business and Economic Statistics, 40, 705-717.

[24]Chen, X.*, Diao, G. and Qin, J.(2020). Pseudo likelihood based estimation and testing of missingpropensity function in nonignorable missing data problems.Scandinavia Journal of Statistics,47,1377-1400.

[23]Lee, J.,Chen, X.and Lam, E.(2020). Testing for change-point in the covariate effects based onthe Cox proportional hazards model.Statistics in Medicine, 39,1473–1488.

[22]Hong. G.,Chen, X., Kang, J. and Li Y.(2020). The Lq-norm learning forultrahigh-dimensionalsurvival data: an integrative framework. Statistica Sinica,30, 1213-1233.

[21]Hu, N.,Chen, X.*and Sun, J.(2020). Semiparametric Analysis of Short-Term and Long-TermHazard Ratio Models with Length-Biased and Right-Censored Data. StatisticaSinica,30, 487-509.

[20]Bai, F.,Chen, X., Chen, Y. and Huang, T.(2019). A General Quantile Residual Life Model forLength-Biased Right-Censored Data. Scandinavia Journal of Statistics,46, 1191-1205.

[19]Chen, X.*, Chen, Y., Wan, A. and Zhou, Y. (2018). On the asymptotic non-equivalence ofefficient-GMM and MEL estimators in models with missing data. Scandinavian Journal of Statistics,46, 361-388.

[18]Chen, X., Li, H, Lin, H, Liang, H.(2019).Functional response regression analysis. Journal of MultivariateAnalysis, 169, 218-233.

[17] Hong,G.,Chen, X., Christiani, D. and Li Y.(2017). Integrated Powered Density: Screening Ultrahigh-DimensionalCovariates with Survival Outcomes. Biometrics,74, 421-429.

[16]Chen, X.and Hu, T and Sun, J(2017). Sieve Maximum Likelihood Estimation for the ProportionalHazards Model under Informative Censoring. Computational Statistics and Data Analysis,112,224-234.

[15]Chen, X*., Hu,N., Sun,J.(2017). Smooth composite likelihood analysis of length-biased andright-censored data with the AFT model. Statistica Sinica, 27,229-242.

[14]Fang, H.,Chen, X., Grant, S., Pei, X. and Tan, M(2015). Experimental design and statistical analysis for three drugs combination studies. Statistical Methods in Medical Research, 26,1261-1280.

[13]Chen,X.*,Liu,Y.,Sun,J. and Zhou, Y.(2016). Semiparametric quantile regression analysis of right-censored and length-biased failure time data with partially linear varying effects. Scandinavian Journal of Statistics, 43, 921-938.

[12]Chen,X.*, Tang,N. and Zhou,Y.(2016). Quantile regression of longitudinal data with informative observation times. Journal of Multivariate Analysis, 144, 176-188.

[11]Chen, X., Wan,A. and Zhou, Y.(2015) Efficient quantile regression analysis with missingobservations. Journal of the American statistical Association, 110, 723-741.

[10] Hu,N.,Chen, X.*and Sun, J(2015). Regression analysis of length-biased and right-censored failure time data with missing covariates. Scandinavian Journal of Statistics, 42, 438-452

[9]Chen, X.*, Sun, J. and Liu, L.(2015) Semiparametric partial Linear quantile regression of longitudinal data with time varying coefficients and informative observation times. Statistics Sinica, 25, 1437-1458.

[8]Chen,X., Wan, A. and Zhou, Y.(2014). A quantile varying-coefficient regressionapproach to length-biased data modeling. Electronic Journal of Statistics, 8, 2514-2540.

[7]Chen, X. and Zhou, Y.(2012) Quantile Regression for Right-Censored and Length-Biased Data. Acta Mathematicae Apllicatae Sinica(English Series) , 28, 443-462.

[6]Zhang,F,Chen, X. and Zhou, Y. Proportional Hazards Models with Varying Coefficients for Right-Censored Length-Biased Data. Lifetime Data Analysis ,20, 132-157.

[5]Ma, Y., Wan, A.,Chen,X. and Zhou, Y. (2013). On estimation and inference in a partially linear hazard model with varying coefficients. Annals of the Institute of Statistical Mathematics, 66, 931-960.

[4]赵晓玲，陈雪蓉，周勇.(2012)基于非参估计的VaR和ES方法的应用研究.《数理统计与管理》,3,381-388.

[3] Li,Y.,Chen, X.and Zhao, L. (2009). Stability and existence of periodic solutions to delayed Cohen-Grossberg BAM neural networks with impulses on time scales. Neurocomputing, 72, 1621-1630.

[2] Li,Y., Zhao, L. andChen, X.(2010). Positive periodic solutions of functional differential equations with impulse on time scales. Journal of Applied Mathematics and Computing, 34, 495-510.

[1] Li,Y., Zhao, L. andChen, X.(2012). Existence of periodic solutions for neutral type cellular neural networks with delays. Applied Mathematical Modelling, 36, 1173-1183.

六、科研项目：

[6]主持国家自然科学基金面上项目：流数据可更新推断与预测研究，No. 12371296, 2024-2027.

[5]主持国家重点研发计划课题“分布式统计学习理论与方法”子课题“隐私保护下分布式数据的稳健统计推断研究”，2022YFA1003702，2022.12-2027.11.

[4]主持国家自然科学基金重点项目“半参数集成回归推断”子项目“函数型数据信号的提取及集成回归推断”，No. 11931014,2020.1-2024.12.

[3] 主持国家自然科学基金面上项目：复杂数据下结构突变模型的统计推断及应用，No.11871402,2019.1-2022.12.

[2] 主持国家自然科学基金青年项目：两类不完全数据下基于秩以及非光滑估计方程的统计推断及其应用，No.11501461,2016.1-2018.12

[1] 主持中央高校基本科研业务费专项资金-年度培育项目：生存数据下变点的统计推断研究，2018.1-2018.12